Multi-objective optimization of green technology thermal drilling process using greyfuzzy logic method
Author(s)
Kumar, R
Hynes, N Rajesh Jesudoss
Pruncu, Catalin
Sujana, J Angela Jennifa
Type
Journal Article
Abstract
The wastage of metal chips from conventional drilling process creates massive environmental pollution. In order to reduce emission pollution, this process should be replaced by the green technology of thermal drilling process. Thermal drilling is an energy efficient, clean and chip less drilling method that has attracted more automotive and aerospace manufacturers in recent years. The processing time, tool failure and manufacturing cost of drilling are reduced and the bushing formation is three times thicker than the workpiece, which offers a prolonged bearing area that fits a shaft firmly. However, achieving these objectives is time consuming and leads to material waste for industrial sectors. Here, we propose a robust methodology that combines experiments with modern optimization technique in order to solve the industrial challenge and further improve the drilling quality. The experiments were conducted on galvanized steel material with different thicknesses (1 mm, 1.5 mm and 2 mm). Three thermal drilling tools are developed using M2 tool steel with three different geometry angles such as , and . The recommended level (A3 B1 C2) identified in this experimental research, allows to minimize the thermal drilling parameters with intended benefits of the output parameters. It permits to identify the best solution of minimum surface roughness of 1.088 μm with the roundness error of 0.080 mm and 0.145 mm run-out. Further, the multi-objective decision technique designed offer contribution details of critical input parameters contribution of rotational speed, tool angle, and workpiece as 76.58%, 10.56%, and 1.982%, respectively.
Date Issued
2019-11-01
Date Acceptance
2019-07-18
Citation
Journal of Cleaner Production, 2019, 236
ISSN
0959-6526
Publisher
Elsevier
Journal / Book Title
Journal of Cleaner Production
Volume
236
Copyright Statement
© 2019 Elsevier Ltd. All rights reserved. This manuscript is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence http://creativecommons.org/licenses/by-nc-nd/4.0/
Subjects
0907 Environmental Engineering
0910 Manufacturing Engineering
0915 Interdisciplinary Engineering
Environmental Sciences
Publication Status
Published
Article Number
ARTN 117711
Date Publish Online
2019-07-21